Optuna is a hyperparameter optimization framework for machine learning models. It can help automate and streamline the process of tuning the hyperparameters. It’s quite popular among Kaggle users and you’ll see it used within competitions. In this article, we will go over an example of using it on a basic dataset. There is also a […]
Ordinal Encoder
In the realm of data science and machine learning, handling categorical data effectively is crucial for building robust predictive models. Categorical data, often representing discrete labels or categories, needs to be converted into numerical formats before feeding into machine learning algorithms Scikit-learn, a powerful and widely-used Python library for machine learning, offers a convenient tool […]
One Hot Encoder
In the realm of machine learning and data science, preparing your data is often as crucial as the modeling itself. One of the essential preprocessing steps when working with categorical data is one-hot encoding. This technique transforms categorical variables into a format that can be provided to machine learning algorithms to improve predictions and insights. […]